Search Results - (( a detection based algorithm ) OR ( defect classification based algorithm ))
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…All the algorithms were pretrained from ImageNet data-base before training with the wafer defect images. …”
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A cascading fuzzy logic with image processing algorithm-based defect detection for automatic visual inspection of industrial cylindrical object’s surface
Published 2018“…This paper proposes a cascading fuzzy logic algorithm with image processing technique for defect detection and classification on the lateral surface of industrial cylindrical object using a camera and multiple flat mirrors. …”
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Detection of tube defect using the autoregressive algorithm
Published 2015“…This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. …”
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Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules
Published 2023“…However, high similarity of characteristics among the shapes and textures has been a major challenge in defect classification process. …”
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Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials
Published 2013“…Therefore, by removmg the low frequency signals, the intemal defect detectability can be improved. Moreover, the classification of an input pattem based on the closest neighbours of the point of interest provides more accurate defect detection in comparison with the classification based on experience data as the defect pattems vary on circumstances in ultrasonic NDE problems.…”
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Intelligent Thermal Condition Monitoring Of Electrical Equipment Using Infrared Thermography
Published 2013“…In this thesis, an automatic features extraction system from thermal image of defects and the intelligent classification of thermal condition based on neural network are proposed. …”
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Assessing the performance of YOLOv5, YOLOv6, and YOLOv7 in road defect detection and classification: a comparative study
Published 2024“…Many works have reported using machine-learning-based object detection algorithms to detect defects, such as cracks in buildings and roads. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Computer aided diagnoses for detecting the severity of Keratoconus
Published 2024“…Conclusion: The algorithm used for extracting the cone base area of the keratoconic cornea at different stages was validated by an ophthalmic specialist to ensure that the cone base area was appropriately extracted. …”
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Identification of weld defect through the application of denoising method to the sound signal acquired during pulse mode laser welding
Published 2023“…This paper describes the improvement of weld defect identification achieved by incorporating Z-score-based thresholding into the wavelet denoising algorithm for the pre-processing of sound signals. …”
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Training feedforward neural networks for fault diagnosis of ball bearing
Published 2018“…Then, a novel CFS-based FNNs approach is applied to classify these ball bearings conditions. …”
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Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The classification algorithm is a popular machine learning approach for software defect prediction. …”
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Vibration Signal for Bearing Fault Detection using Random Forest
Published 2024“…Based on the chosen properties of an induction motor, a random forest (RF) classifier, a machine learning technique, is examined in this study for bearing failure detection. …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…The objective of the work was to find the best combination of SVM parameters and data features to maximize defect classification accuracy. The paper presents the results obtained to demonstrate the strengths of the Bees Algorithm as an optimization tool.…”
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Neural network paradigm for classification of defects on PCB
Published 2003“…The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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